2 citations · 2 across the 4 of their papers we have counts for
4 papers
Small-supercell and Small-dataset Training Strategy of Machine Learning Interatomic Potentials for Point Defects
Zhenxing Dai, Mingjue Ni, Xinpeng Li +3
Machine learning interatomic potentials (MLIPs) can treat large-scale material systems with near first-principles accuracy and have been widely used to accelerate point-defect simu…
Substitutional platinum as an efficient nonradiative recombination center in silicon
Zhenxing Dai, Menglin Huang, Xin-Gao Gong +1
Platinum (Pt) is widely used for carrier-lifetime control in silicon power devices, yet the microscopic nonradiative recombination mechanism of the substitutional platinum ($\text{…
Machine learning Hamiltonian enables scalable and accurate defect calculations: The case of oxygen vacancies in amorphous SiO
Zhenxing Dai, Zhong Yang, Mingjue Ni +4
Point defects critically influence the properties of materials and devices, yet density functional theory (DFT) remains computationally demanding for defect supercell calculations.…
Fractional Quantum Multiferroics from Coupling of Fractional Quantum Ferroelectricity and Altermagnetism
M. Q. Dong, B. Liu, Z. H. Dai +3
Multiferroics, which combine ferroelectric and magnetic order, offer a transformative platform for next-generation electronic devices. However, the intrinsic competition between th…